{ "_id": "6a28d1c7732311cd8758d133", "Package": "ebrahim.gof", "Type": "Package", "Title": "Ebrahim-Farrington Goodness-of-Fit Test for Logistic Regression", "Version": "2.0.0", "Date": "2026-06-10", "Authors@R": "person(\"Ebrahim\", \"Khaled Ebrahim\",\nemail = \"ebrahimkhaled@alexu.edu.eg\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0006-7839-8778\"))", "Maintainer": "Ebrahim Khaled Ebrahim ", "Description": "Implements the Ebrahim-Farrington goodness-of-fit test for\nlogistic regression models, particularly effective for sparse\ndata and binary outcomes. This test provides an improved\nalternative to the traditional Hosmer-Lemeshow test by using a\nmodified Pearson chi-square statistic with data-dependent\ngrouping. The test is based on Farrington (1996) theoretical\nframework but simplified for practical implementation with\nbinary data. Includes functions for both the original\nFarrington test (for grouped data) and the new\nEbrahim-Farrington test (for binary data with automatic\ngrouping), the Directed Ebrahim-Farrington (DEF) test that\ntargets calibration-shape departures, and an ensemble that\ncombines the DEF bases via the Cauchy combination test. For\nmore details see Hosmer (1980) \nand Farrington (1996) .", "License": "GPL-3", "URL": "https://github.com/ebrahimkhaled/ebrahim.gof", "BugReports": "https://github.com/ebrahimkhaled/ebrahim.gof/issues", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "VignetteBuilder": "knitr", "Repository": "https://ebrahimkhaled.r-universe.dev", "Date/Publication": "2026-06-09 23:12:52 UTC", "RemoteUrl": "https://github.com/ebrahimkhaled/ebrahim.gof", "RemoteRef": "HEAD", "RemoteSha": "fd8b2556d4fb92876d0986104c34ec16dfaf2896", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-10 02:48:31 UTC", "User": "root" }, "Author": "Ebrahim Khaled Ebrahim [aut, cre] (ORCID:\n)", "MD5sum": "8a14f2efb3f49e4f9d3004f3d5cb459a", "_user": "ebrahimkhaled", "_type": "src", "_file": "ebrahim.gof_2.0.0.tar.gz", "_fileid": "b102d9ff712378e29f0e00c5212e9c100ffc36854401fd8b82b747421655f7fd", "_filesize": 519037, "_sha256": "b102d9ff712378e29f0e00c5212e9c100ffc36854401fd8b82b747421655f7fd", "_created": 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